基于扩展卡尔曼滤波的无人机辅助定位研究  

UAV-Aided Localization Based on Extended Kalman Filtering

作　　者：程擎[1] 李怡恒 鲁合德 CHENG Qing;LI Yiheng;LU Hede(Civil Aviation Flight University of China,Guanghan 618000,China)

机构地区：[1]中国民用航空飞行学院,四川广汉618000

出　　处：《电光与控制》2023年第12期93-97,103,共6页Electronics Optics & Control

基　　金：交通运输工程优势特色学科建设(D202103);民航飞行技术与飞行安全重点实验室开放项目(FZ2021KF07);四川省大学生创新创业训练计划(S202210624104)。

摘　　要：面对城市低空复杂的电磁环境,无人机在运行过程中GNSS信号极易受到干扰,导致定位不准。为提高无人机定位精度,提出一种基于扩展卡尔曼滤波的数据融合方法,该方法在惯性导航系统的基础上,与基于5G信号的三维定位相融合,并对惯性导航误差进行修正。软件仿真表明,该方法在缺少有效GNSS信号的情况下将姿态误差和位置误差控制在一定的范围内,提高了无人机的定位精度,视距下的平均位置误差为16.6 cm,相比于融合前定位精度提升了49.7%,使得无人机具有长时间较高定位精度,具有一定的工程实用性。Faced with complex electromagnetic environment of urban low-altitude areas,GNSS signals are prone to be interfered during UAV operation,leading to inaccurate positioning.In order to improve the accuracy of UAV positioning,a data fusion method based on extended Kalman filtering is proposed.Based on the inertial navigation system,the fusion with 3D positioning based on 5G signals is conducted,and inertial navigation errors are corrected by using the fused data.The software simulation shows that the attitude error and the position error are limited within a certain range in the absence of effective GNSS signals,and the accuracy of UAV positioning is improved.The average position error under sight distance is 16.6 cm,and the positioning accuracy is improved by 49.7%compared with that before fusion.The UAV's ability to have high positioning accuracy for a long duration is realized,and the method has certain engineering practicality.

关 键 词：无人机 组合定位 扩展卡尔曼滤波 5G 

分 类 号：TN92[电子电信—通信与信息系统]